A Dynamic Incentive Mechanism for Transmission Expansion in Electricity Networks: Theory, Modeling, and Application

We propose a price-cap mechanism for electricity-transmission expansion based on redefining transmission output in terms of financial transmission rights. Our mechanism applies the incentive-regulation logic of rebalancing a two-part tariff. First, we test this mechanism in a three-node network. We show that the mechanism intertemporally promotes an investment pattern that relieves congestion, increases welfare, augments the Transco´s profits, and induces convergence of prices to marginal costs. We then apply the mechanism to a grid of northwestern Europe and show a gradual convergence toward a common-price benchmark, an increase in total capacity, and convergence toward the welfare optimum.Electricity transmission expansion, incentive regulation

Preliminary specification and design documentation for software components to achieve catallaxy in computational systems

This Report is about the preliminary specifications and design documentation for software components to achieve Catallaxy in computational systems. -- Die Arbeit beschreibt die Spezifikation und das Design von Softwarekomponenten, um das Konzept der Katallaxie in Grid Systemen umzusetzen. Eine Einführung ordnet das Konzept der Katallaxie in bestehende Grid Taxonomien ein und stellt grundlegende Komponenten vor. Anschließend werden diese Komponenten auf ihre Anwendbarkeit in bestehenden Application Layer Netzwerken untersucht.Grid Computing

Transmission congestion management by optimal placement of FACTS devices

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 13/09/2010.This thesis describes the implementation of the Flexible AC Transmission Systems (FACTS) devices to develop a market-based approach to the problem of transmission congestion management in a Balancing Market. The causes, remedies and pricing methods of transmission congestion are briefly reviewed. Balancing Market exists in markets in which most of the trading is done via decentralized bilateral contracts. In these markets only final adjustments necessary to ensure secure system operation is carried out at a centralized Balancing Market. Each market player can participate in the Balancing Market by submitting offers and bids to increase and decrease its initially submitted active generation output. In this research a method is proposed to reduce costs associated with congestion re-dispatch in a Balancing Market by optimal placement of FACTS devices, and in particular Thyristor Controlled Phase Shifter Transformers (TCPST). The proposed technique is applicable to both Mixed Integer Linear Programming (MILP) and Mixed Integer Non-Linear Programming (MINLP). In the MILP a power system network is represented by a simplified DC power flow under a MILP structure and the Market participants' offers and bids are also represented by linear models. Results show that applications of FACTS devices can significantly reduce costs of congestion re-dispatch. The application of the method based on the MINLP creates a nonlinear and non-convex AC OPF problem that might be trapped in local sub-optima solutions. The reliability of the solution that determines the optimal placement of FACTS devices is an important issue and is carried out by investigation of alternative solvers. The behavior of the MINLP solvers is presented and finally the best solvers for this particular optimization problem are introduced. The application of DC OPF is very common in industry. The accuracy of the DC OPF results is investigated and a comparison between the DC and AC OPF is presented

Financial risk management and market performance in restructured electric power markets: Theoretical and agent-based test bed studies

Electric power systems have traditionally been operated as natural monopolies. Restructuring has entailed un-bundling of hitherto vertically integrated organizations into independently managed generation, transmission and distribution systems. As a result, electric power markets can be divided into wholesale and retail layers. The wholesale power market design proposed by the U.S. Federal Energy Regulatory Commission (FERC) in an April 2003 white paper FERC (2003) encompasses the following core features: central oversight by an independent system operator (ISO); a two-settlement system consisting of a day-ahead market supported by a parallel real-time market to ensure continual balancing of electric power supply and demand. In this new environment electricity is traded like other commodities in ISO organized power pools. However, power systems must be in instantaneous power balance, i.e. demand must equal supply at all times. Moreover, at present, electric power cannot be stored economically in substantial amounts. The power flows on transmission systems are governed by physical laws of power flow such as the Kirchoff\u27s law, and are constrained by the overall capacity of transmission lines. During the peak hours of electric power demand, the above mentioned constraints become binding affecting outcomes throughout the grid. Transmission constraints in particular create congestion, which can impede the generation and/or injection of electric power into the grid in merit-order , i.e., from least-cost generator to high-cost generators. Electric power prices can be very volatile and hence, new forms of risk have arisen due to the restructuring. As part of restructuring, congestion on electricity transmission grids is now handled in many energy regions by means of locational marginal pricing (LMP), i.e., the pricing of electric energy in accordance with the location of its injection or withdrawal from the grid. The LMP so calculated at a node k measures the least cost to supply an additional unit of load at that location from the resources of the system. The difference in LMPs at any two buses is known as congestion rent, which is collected by the ISO. In the case of grid congestion, LMPs can vary widely across the grid, which creates price risk for all market participants. Using existing market design features, this thesis investigates the risk management issues of market participants and overall efficiency of the wholesale power markets. Additionally, I also study the market rules dealing with renewable energy sources

Market and Economic Modelling of the Intelligent Grid: End of Year Report 2009

The overall goal of Project 2 has been to provide a comprehensive understanding of the impacts of distributed energy (DG) on the Australian Electricity System. The research team at the UQ Energy Economics and Management Group (EEMG) has constructed a variety of sophisticated models to analyse the various impacts of significant increases in DG. These models stress that the spatial configuration of the grid really matters - this has tended to be neglected in economic discussions of the costs of DG relative to conventional, centralized power generation. The modelling also makes it clear that efficient storage systems will often be critical in solving transient stability problems on the grid as we move to the greater provision of renewable DG. We show that DG can help to defer of transmission investments in certain conditions. The existing grid structure was constructed with different priorities in mind and we show that its replacement can come at a prohibitive cost unless the capability of the local grid to accommodate DG is assessed very carefully.Distributed Generation. Energy Economics, Electricity Markets, Renewable Energy

Decentralised Optimisation and Control in Electrical Power Systems

Emerging smart-grid-enabling technologies will allow an unprecedented degree of observability and control at all levels in a power system. Combined with flexible demand devices (e.g. electric vehicles or various household appliances), increased distributed generation, and the potential development of small scale distributed storage, they could allow procuring energy at minimum cost and environmental impact. That however presupposes real-time coordination of demand of individual households and industries down at the distribution level, with generation and renewables at the transmission level. In turn this implies the need to solve energy management problems of a much larger scale compared to the one we currently solve today. This of course raises significant computational and communications challenges. The need for an answer to these problems is reflected in today’s power systems literature where a significant number of papers cover subjects such as generation and/or demand management at both transmission and/or distribution, electric vehicle charging, voltage control devices setting, etc. The methods used are centralized or decentralized, handling continuous and/or discrete controls, approximate or exact, and incorporate a wide range of problem formulations. All these papers tackle aspects of the same problem, i.e. the close to real-time determination of operating set-points for all controllable devices available in a power system. Yet, a consensus regarding the associated formulation and time-scale of application has not been reached. Of course, given the large scale of the problem, decentralization is unavoidably part of the solution. In this work we explore the existing and developing trends in energy management and place them into perspective through a complete framework that allows optimizing energy usage at all levels in a power system